The present disclosure generally relates to energy conservation in a building. The present disclosure relates more specifically to generating an energy use model for a building using one characteristic of the building, such as the building's water consumption, as a proxy for another characteristic, such as the building's occupancy, within the building's energy use model.
Many commercial buildings today are equipped with a variety of energy-consuming devices. For example, a commercial building may be equipped with various heating, ventilation, and air conditioning (HVAC) devices that consume energy to regulate the temperature in the building. Other exemplary types of building equipment that consume energy may include lighting fixtures, security equipment, data networking infrastructure, and other such equipment.
The energy efficiency of commercial buildings has become an area of interest in recent years. In many areas of the world, electrical generation and transmission assets have or are reaching full capacity. Because commercial buildings consume a good portion of the generated electricity in the United States and elsewhere, a major strategy for solving energy grid problems is to implement energy conservation measures (ECMs) within buildings. ECMs may also provide a financial benefit to the operator of a building, since the cost for the building's energy consumption can be reduced by implementing ECMs.
In general, ECMs involve first identifying potential areas of improvement and then taking the appropriate corrective measures. For example, the energy consumption of a building's lighting may be identified as a potential area of improvement and energy-efficient lighting may be installed in the building as an ECM. To identify potential areas of improvement, various metrics may be obtained regarding the building's energy consumption. For example, the building's energy consumption, typically measured in megawatt-hours (MWh), or the building's energy demand, typically measured in megawatts (MW), may be recorded and analyzed to identify trends and patterns in the building's energy use. A technician trained to analyze such data may then review the metrics for the building and suggest the implementation of one or more ECMs.
Numerous factors may affect a building's energy usage profile (e.g., the building's energy consumption and demand). For example, a building's energy use may be affected by the weather (e.g., more energy may be needed to heat the building on a cold day and vice-versa), the building's occupancy, the day of the week (e.g., more energy may be consumed during the workweek than on a weekend), and other such factors. These factors may independently affect the energy usage profile of the building or may be interrelated. For example, the occupancy of the building may drop on the weekend or during a major snowstorm. Thus, the energy needs of a building at any given time must be put into context before a meaningful analysis can be performed.
Identifying potential areas for improvement to a building's energy efficiency may involve a degree of uncertainty, particularly with regard to the potential cost savings realized by implementing an ECM. In some cases, information regarding the factors that affect a building's energy usage profile may not be available or fully known. For example, the occupancy of a commercial building may not be known precisely, unless the building is a secure environment (e.g., each person that enters or exits the building must pass through a security checkpoint, scan a security badge, etc.). Variations in the factors over time may also lead to potential estimation errors. Because of this uncertainty, some ECM providers, such as companies that sell energy-efficient building equipment, guarantee the financial savings to a commercial building's operator. Any energy or cost savings shortfalls that are realized after installation of the upgraded equipment may be borne by the ECM provider. Thus, an accurate energy use model for a building may decrease potential liability for an ECM provider and create realistic expectations of the building's operator regarding the implementation of ECMs.